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In practical two-sided matching problems, every agent usually cares about the matching result. If the result reaches or exceeds his/her expectation, he/she will experience elation; otherwise, he/she will experience disappointment. This is the psychological behavior of agents in two-sided matching, and the satisfaction degrees to the potential matching result of agents are closely related to the psychological behavior. However, the psychological behavior of agents is missing in the existing two-sided matching methods. The purpose of this paper is to develop a method for the two-sided matching problem considering psychological behavior of agents on both sides. First, the expected preference ordinals of each agent toward opposite agents are calculated based on the uncertain preference ordinals provided by agents. Then, the preference utility function is constructed, and the expected preference ordinals are transformed into preference utility values using the preference utility function. Next, based on the disappointment theory, the modified preference utility values are determined by calculating the disappointment values and elation values of each agent to the possible matching results. Furthermore, to maximize the sum of modified preference utility values of all agents on each side, a bi-objective optimization model is constructed, and the satisfied matching result can be obtained by solving the optimization model. Finally, a numerical example is used to illustrate the use of the proposed method. [ABSTRACT FROM AUTHOR]

Large group decision-making (LGDM) is a special group decision-making (GDM) problem, in which a large number of persons take part in decision process, while research concerning this issue is still relatively scarce. The objective of this paper is to develop a method to solve the LGDM problem, in which a large number of persons from multiple groups take part in the decision process and express their personal evaluations on the alternatives according to the pre-established identifier set. In the method, the percentage distribution on evaluations of each group concerning each alternative is determined. The decision weight of each group concerning each alternative is obtained by aggregating the subjective weight, which is provided by the organizer, and the objective weight, determined according to the level of consensus among participators' evaluations. According to the percentage distributions and decision weights, the dominance degrees on pairwise comparisons of alternatives are calculated, and a ranking of alternatives can be determined using the PROMETHEE II method. Finally, an example is given to illustrate the use of the proposed method. [ABSTRACT FROM AUTHOR]

Psychological perception of agents on both sides is an important factor that should not be ignored in two-sided matching problem. Few studies have focused on this issue that how to describe the psychological behavior of agents on both sides according to behavioral decision theory and introduce it into the two-sided matching model. In this paper, a stable two-sided matching method considering psychological behavior of agents on both sides is proposed to solve the two-sided matching problems, in which the preference ordinal number information is provided by agents on both sides. Firstly the preference ordinal numbers provided by agents on both sides are transformed into preference utility values. Then, according to disappointment theory, the perception utility values are calculated by modifying the preference utility values. For maximizing the sum of perception utility values of agents on each side, a multi-objective optimization two-sided matching model is developed considering the stable matching condition. The weighted sums method based on membership function is used to convert the multi-objective optimization model into a single-objective optimization model, and the optimal two-sided matching result can be obtained by solving the model. Finally, an example is given to illustrate the practicality and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: Customer response modeling is essential for a firm to allocate the marketing resources to active customers who have potential values. With the development of social media, customer response modeling in social media plays important roles in the firms’ marketing decisions. For customer response modeling in social media, the inputs involve multiple types of data and the purposes are to identify respondents to multiple items. In this study, a multi-task multi-kernel transfer learning (MT-MKTL) method is proposed to integrate shared, task-specific and transferred features in a framework for customer response modeling in social media. A two-phase algorithm is applied to solving the MT-MKTL problem. A computational experiment is conducted on microblog data. The experimental results show that the MT-MKTL method exhibits good performance. [Copyright &y& Elsevier]

In some practical risky decision making problems, the psychological behavior of the decision maker (DM) should be considered. Thus, how to introduce behavioral decision theory into risky decision analysis deserves more attention. In the situation of considering the DM's psychological behavior, a decision analysis method based on regret theory is proposed to solve the risky multiple attribute decision making problem, where attribute values and probabilities of the states are both in the form of interval numbers. Based on regret theory, utility values and regret values concerning attribute values are calculated, respectively. Then, by calculating the sum of utility value and regret value of each alternative, the DM's perceived utility value is obtained. Further, by constructing a programming model which satisfies maximum overall perceived utility values of alternatives and solving the model, a ranking of alternatives can be determined. Finally, two numerical examples are used to illustrate the feasibility and validity of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a novel method for solving the stochastic multiple attribute decision making (SMADM) problem, where consequences of alternatives with respect to attributes are represented by random variables with cumulative distribution functions. First, the concepts of ideal and anti-ideal cumulative distribution functions are introduced, and the related theoretical analysis is given. Next, according to the concept of classical TOPSIS, the ideal and anti-ideal points of the SMADM problem are determined, which are in the form of cumulative distribution function vectors. Then, the closeness coefficient of each alternative is obtained by calculating the distances to the ideal and anti-ideal points, simultaneously. Based on the obtained closeness coefficients, a ranking of alternatives is determined. Finally, two numerical examples are given to illustrate the use of the proposed method. [Copyright &y& Elsevier]

In this paper, a method based on prospect theory is proposed to solve the multiple attribute decision making (MADM) problem with three formats of attribute aspirations. According to the idea of prospect theory, reference points concerning attributes are first determined. Then, for the three formats of attribute aspirations, the calculation formulae of alternatives' gains/losses concerning attributes are given. By calculating each alternative's gain/loss, a gain-loss matrix is constructed. Further, using the value function from prospect theory and the simple additive weighting method, the overall prospect value of each alternative is calculated. Based on the obtained overall prospect values, a ranking of alternatives can be determined. Finally, a case study is given to illustrate the use of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) is a method for solving the multiple attribute decision making (MADM) problem considering decision maker’s (DM’s) behavior, in which the attribute values are in the format of crisp numbers. It cannot be used to handle hybrid MADM problems with various formats of attribute values. In this paper, an extended TODIM method is proposed to solve the hybrid MADM problem. First, three formats of attribute values (crisp numbers, interval numbers and fuzzy numbers) are expressed in the format of random variables with cumulative distribution functions. Then, according to the concept of the classical TODIM method, the gain and loss matrices concerning each attribute are constructed by calculating the gain and loss of each alternative relative to the others. Further, by calculating the dominance degree of each alternative over the others, the overall value of each alternative can be obtained to rank the alternatives. Finally, two numerical examples are used to illustrate the use of the proposed method. [Copyright &y& Elsevier]

This paper proposes a method to solve the multiple attribute decision making (MADM) problem with normal random variables. Firstly, a simple approach for identifying the stochastic dominance relation between a pair of normal random variables based on the expectations and variance values is given by theoretical analysis. Then, the dominance relation matrix with regard to each attribute is built according to the simple approach. Furthermore, ELECTRE III method is used to obtain the ranking result of alternatives. Finally, a numerical example is used to illustrate the feasibility and validity of proposed method. [ABSTRACT FROM AUTHOR]

With respect to the situations that response actions will intervene evolvement of emergency and cause different life and property losses, this paper proposes a risk decision analysis method for emergency response based on prospect theory. First, the description of risk decision problem of emergency response is given. Then, based on main idea of prospect theory, the values of possible scenarios of emergency are calculated, i.e., describe the decision maker's psychological feeling on the life and property losses quantitatively. Furthermore, the weights of possible scenarios of emergency are calculated, i.e., describe the decision maker's psychological feeling on the important degree of possible scenarios quantitatively. Moreover, according to the values, weights and alternative cost, the overall prospect value of each alternative is calculated to determine a ranking of alternative. Finally, a case study is given to illustrate the feasibility and validity of the proposed method. [ABSTRACT FROM AUTHOR]

The decision making trial and evaluation laboratory (DEMATEL) method is a useful tool for analyzing correlations among factors using crisp values. However, the crisp values are inadequate to model real-life situations due to the fuzziness and uncertainty that are frequently involved in judgments of experts. The aim of this paper is to extend the DEMATEL method to an uncertain linguistic environment. In this paper, the correlation information among factors provided by experts is in the form of uncertain linguistic terms. A formula is first presented to transform correlation information from uncertain linguistic terms to trapezoidal fuzzy numbers. Then, we aggregate the transformed correlation information of each expert into group information using the operations of trapezoidal fuzzy numbers. The importance and classification of factors are determined via fuzzy matrix operations. Furthermore, a causal diagram is constructed to vividly show the different roles of factors. Finally, an example is used to illustrate the procedure of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: Risk factor identification of IT outsourcing is significant to capture the source of IT outsourcing risk. Risk factors of IT outsourcing are often interdependent, and consequently the interrelationships among factors affect risk factor identification, whereas this fact is neglected in the existing studies. The purpose of this paper is to investigate a method for identifying risk factors of IT outsourcing, in which the interrelationships among risk factors are considered. Firstly, the risk factors of IT outsourcing are figured out through literature review and expert interview. Then, the interrelationships among risk factors and relative analysis are given. Furthermore, based on the 2-tuple fuzzy linguistic representation model and the classical Decision Making Trial and Evaluation Laboratory (DEMATEL) method, an extended DEMATEL method is developed to identify the importance together with the classification of risk factors. Finally, the potential of the proposed method is shown through an illustrative example of a Chinese resource company. [Copyright &y& Elsevier]

The member selection is an important decision problem in the formation of R&D teams. Selecting suitable members will facilitate the success of R&D projects. In the existing methods for partner selection, the individual information to measure the individual performance of members is mostly used, while the collaborative information to measure the collaborative performance between members is seldom considered. Therefore, this paper proposes a method for member selection of R&D teams, in which both the individual information of members and the collaborative information between members are considered. In order to select desired members, a bi-objective 0-1 programming model is built using the individual and collaborative information. To solve the model, a multi-objective genetic algorithm is developed since the model is NP-hard. A practical example followed by simulation experiment is used to illustrate the applicability of the proposed method. Additionally, the experimental results show that the proposed method can support satisfactory and high quality member selection. [Copyright &y& Elsevier]

In this paper, a new approach is proposed to solve group decision making (GDM) problems where the preference information on alternatives provided by decision makers (DMs) is represented in incomplete fuzzy preference relations. In order to make the collective opinion close each decision maker's opinion as near as possible, an optimization model is constructed to integrate the incomplete fuzzy preference relations and to compute the collective ranking values of alternatives. The ranking of alternatives or selection of the most desirable alternative(s) is directly obtained from the derived collective ranking values. A numerical example is also used to illustrate the applicability of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper investigates the multiple attribute decision making (MADM) problem with preference information on alternatives. A new approach is proposed to solve the MADM problem, where the decision maker gives his/her preference on alternatives in a fuzzy relation. To reflect the decision maker''s preference information, an optimization model is constructed to assess the attribute weights and then to select the most desirable alternatives. Finally, an example is used to illustrate the proposed approach. [Copyright &y& Elsevier]

Online product reviews have significant impacts on consumers’ purchase decisions. To support consumers’ purchase decisions, how to rank the products through online reviews is a valuable research topic, while research concerning this issue is still relatively scarce. This paper proposes a method based on the sentiment analysis technique and the intuitionistic fuzzy set theory to rank the products through online reviews. An algorithm based on sentiment dictionaries is developed to identify the positive, neutral or negative sentiment orientation on the alternative product concerning the product feature in each review. According to the identified positive, neutral and negative sentiment orientations, an intuitionistic fuzzy number is constructed for representing the performance of an alternative product concerning a product feature. The ranking of alternative products is determined by intuitionistic fuzzy weighted averaging (IFWA) operator and preference ranking organization methods for enrichment evaluations II (PROMETHEE II). A case study is given to illustrate the use of the proposed method. The comparisons and experiments are further conducted to illustrate the characteristics and advantages of the proposed method. Converting the identified positive, neutral and negative sentiment orientations into intuitionistic fuzzy numbers is a new idea for processing and fusing a large number of sentiment orientations of online reviews. Based on the proposed method, decision support system can be developed to support the consumers’ purchase decisions more conveniently. [ABSTRACT FROM AUTHOR]

Highlights: [•] The method is presented to combine multi-source decision knowledge. [•] Rule-based ontology reasoning is presented to support decision-makings. [•] The semantic interoperable decision environment is enabled. [•] The decision knowledge is evolved and updated as time goes by. [•] Practices of China’s iron and steel industry can be improved based on this study. [ABSTRACT FROM AUTHOR]

Abstract: Collaborative R&D projects that are applied by innovative research teams (CIRT projects) are supported by government funding agencies in a number of countries due to the complexity and multidiscipline research of innovation. Government funding agencies invest heavily to CIRT projects every year. Thus, it is important to select the desired CIRT projects to avoid undesirable budget consumed. The purpose of this paper is to propose an integrated method for CIRT project selection. In this method, competitiveness and collaboration of candidate innovative research teams (IRTs) are used to assess and select projects. The criteria for competitiveness and collaboration are finalized in light of literature review as well as real situations. A formal decision procedure that aggregates competitiveness and collaboration performances of CIRTs is then presented. It integrates analytic hierarchy process (AHP), scoring method and weighted geometric averaging method. Some sample data from the National Natural Science Foundation of China (NSFC) is used to illustrate the potential application of the proposed method. [ABSTRACT FROM AUTHOR]